Bioflux Analyses

Tobias Weise; Bettina Boettcher; Slavena Vylkova

Feb 06, 2020

Version 2

Bioflux Analyses V.2

DOI

dx.doi.org/10.17504/protocols.io.bb7qirmw

Tobias Weise¹,
Bettina Boettcher²,
Slavena Vylkova²

¹BioControl Jena GmbH, Jena, Germany;
²Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute, Jena, Germany

Tobias Weise

BioControl Jena GmbH

DOI: dx.doi.org/10.17504/protocols.io.bb7qirmw

Collection Citation: Tobias Weise, Bettina Boettcher, Slavena Vylkova 2020. Bioflux Analyses. protocols.io https://dx.doi.org/10.17504/protocols.io.bb7qirmw

Manuscript citation:

This work was supported by the German Ministry for Education and Science in the program Unternehmen Region (BMBF 03Z2JN11).

License: This is an open access collection distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Protocol status: Working

We use this protocol and it's working

Created: February 05, 2020

Last Modified: February 06, 2020

Collection Integer ID: 32720

Keywords: Candida Albicans, Biofilm, Biofilm Formation, Growth Rate, Image Preprocessing, Edge Detection, ODE Model, Parameter Estimation

Abstract

Biofilm formation under shear flow conditions was monitored using the Bioflux1000 device (Fluxion Biosciences, Inc.). In short, Candida albicans overnight cultures were washed in pre-warmed RPMI medium. Cells were seeded for 2-5 sec from the outlet well into the channels of Bioflux1000 flow chambers, which were primed before with warm medium. The cells were allowed to adhere to the channels for 90 min without any flow, followed by removal of non-adherent cells by flowing fresh, pre-warmed RPMI medium for 5 sec. Shear flow was set for time series experiments over 24 h biofilm formation and images were captured every 20 min. Two channels were investigated in parallel having a 10 × magnification to allow a direct comparison between a mutant and a reference (wild type) strain. Image capturing and stacks to movies was performed using the MetaMorph® Software (Molecular Devices).

Source material provided as AVI files was converted into single TIFF images as well as data frames containing meta data annotations. The individual image contains two growth chambers (wild type and mutant) separated by four edge lines. Images were rotated automatically to vertical alignment in order to carry out an automated chamber detection and analysis. The mean pixel intensity (i. e. grey scale value; reflecting cell density) of the individual chamber was calculated and added into the respective data frame. 

An ODE model reflecting the logistic growth as well as the lag phase was fitted to the individual experiments. Fitting was carried out by minimising a cost function (unweighted least-squares-based) using the Nelder-Mead algorithm. Growth rate time series generated from the fitted model were used to compare wild type and mutant regarding the maximum observed growth rates at their respective time points.

All computations were performed using the programming language python (version 3.6.9) and the additional packages numpy (version 1.16.2), opencv-python (version 4.1.1.26), pandas (version 0.25.0), scipy (version 1.3.1) and scikit-image (version 0.15.0).